Digital audio signal processing method and apparatus

ABSTRACT

Compression of audio signal data is described herein. In various embodiments, the compression of each unit of the audio signal data includes the employment of a distribution substantially representative of a subblock of residual data of the unit of audio signal data, to reduce the amount of data having to be transmitted to transmit the unit of audio signal data to a recipient.

RELATED REFERENCES

This application is a Continuation of prior application Ser. No.10/988,807 (pending), filed Nov. 15, 2004, titled “DIGITAL AUDIO SIGNALCOMPRESSION METHOD AND APPARATUS,” and naming the inventor Yuriy A.Reznik. Prior application Ser. No. 10/988,807 is a Continuation-In-Partof application Ser. No. 10/826,469, filed Apr. 16, 2004, which claimsthe benefit of priority to Provisional Application No. 60/464,068, filedApr. 18, 2003, entitled “Noiseless Compression of PCM Audio Signals.”

Prior application Ser. No. 10/988,807 also claims the benefit ofpriority to Provisional Application No. 60/587,731, filed Jul. 13, 2004,entitled “Digital Audio Signal Compression Method and Apparatus.” Theabove-cited applications are incorporated by reference in theirentireties as if fully set forth herein and for all purposes.

FIELD

The present invention relates to the field of signal processing. Morespecifically, the present invention relates to compression of audiosignal data.

BACKGROUND

Digital audio has a number of advantages over analog audio. Inparticular, pulse code modulation (PCM) audio has a number of advantagesover other audio formats. For example, digital audio, in particular, PCMaudio, offers freedom to interchange audio data without generation lossbetween media. Increasingly, PCM audio is not only being offered frommedium like compact disc (CD), it is also widely employed in broadcastprogramming, through air waves or cable, or in streamed contents,through private and/or public networks, such as the Internet.

For broadcast programming or streamed contents, bandwidthavailability/consumption remains a significant challenge.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention will be described by way of exemplary embodiments,but not limitations, illustrated in the accompanying drawings in whichlike references denote similar elements, and in which:

FIG. 1 illustrates a method view for compressing audio signal data, inaccordance with some embodiments of the present invention;

FIG. 2 illustrates a system, including its transmit and receivesections, in accordance with some embodiments;

FIG. 3 illustrates a method view for compressing the residual samples inaccordance with some embodiments of the present invention.

DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

Illustrative embodiments of the present invention include, but are notlimited to, method to compress digital audio data (in particular, PCMaudio data), encoders/decoders adapted to practice all or portions ofthe method, and systems having the encoders/decoders.

In the description to follow, for ease of understanding, the presentinvention will primarily be described in the context of PCM audioembodiments, however, the present invention may be practiced for otherdigital audio, e.g. one-bit oversampled audio representations commonlyused in super-audio compact disks (SACD).

Various aspects of embodiments of the present invention will bedescribed. However, various embodiments may be practiced with only someor all of the described aspects. For purposes of explanation, specificnumbers, materials and configurations are set forth in order to providea thorough understanding of the embodiments being described. Inalternate embodiments, they may be practiced without the specificdetails. In various instances, well-known features are omitted orsimplified in order not to obscure the essence of the embodiments.

Parts of the description will be presented in signal processing terms,such as data, filtering, quantization, encoding, decoding, and so forth,consistent with the manner commonly employed by those skilled in the artto convey the substance of their work to others skilled in the art. Aswell understood by those skilled in the art, the data quantities takethe form of electrical, magnetic, or optical signals capable of beingstored, transferred, combined, and otherwise manipulated throughmechanical, electrical and/or optical components of a general/specialpurpose computing device/system.

The term “computing device/system” as used herein includes generalpurpose as well as special purpose data processing machines, systems,and the like, that are standalone, adjunct or embedded. Examples ofgeneral purpose “computing devices/systems” include, but are not limitedto, handheld computing devices (palm sized, tablet sized and so forth),laptop computing devices, desktop computing devices, servers, and soforth. Examples of special purpose “computing device/system” include,but are not limited to, processor based wireless mobile phones, handhelddigital music players, set-top boxes, game boxes/consoles, CD/DVDplayers, digital cameras, digital CAMCORDERs, and so forth. [DVD—DigitalVersatile Disk]

Various operations will be described as multiple discrete operations inturn, in a manner that is most helpful in understanding the variousembodiments of the present invention, however, the order of descriptionshould not be construed as to imply that these operations arenecessarily order dependent. In particular, these operations need not beperformed in the order of presentation.

The phrase “in one embodiment” is used repeatedly. The phrase generallydoes not refer to the same embodiment; however, it may. The terms“comprising”, “having” and “including” are synonymous, unless thecontext dictates otherwise.

Referring now to FIG. 1, wherein a method view of the present invention,in accordance with some embodiments, is illustrated. As illustrated, forthe embodiments, the process 100 starts with the receiving 102 of aportion of a stream of audio signal data (e.g. PCM audio signal data).On receipt, or shortly thereafter, the audio signal data is partitioned104 into a number of data blocks for subsequent processing(compression). In various embodiments, the audio signal data ispartitioned 104 into a number of fixed or variable size data blocks, andwhen variable sized-blocks are used, the variable data block sizes areconveyed 108 to the recipient (e.g. multiplexed 128 onto thetransmission bit stream). For the embodiments, the default fixed datablock size is assumed to be known to the recipient, however, in otherembodiments, the invention may nonetheless be practiced including theconveyance of the fixed data block size to the recipient (e.g.multiplexed 128 onto the transmission bit stream).

For the embodiments, the data blocks are selected 106 one block at atime, and the remaining operations of process 100 are applied to thecurrently selected data block to process and compress the data block,and ultimately, after compression, placing 128 the processed/compresseddata onto the transmission bit stream for transmission to a recipient.The operations are repeated until all data blocks of the receivedportion of the audio signal have been processed (compressed), andmultiplexed 128 onto the transmission bit stream.

In alternate embodiments, each data block may be further partitionedinto sub-blocks, with the sub-blocks being selected for processing(compression) and multiplexed 128 onto the transmission bit stream, onesub-block at a time. Likewise, for these embodiments, the sub-block sizemay be fixed or variable. Regardless, the sub-block size is conveyed toa recipient. For these embodiments, the operations are also repeateduntil all sub-blocks of the data block have been processed (compressed)and multiplexed 128 onto the transmission bit stream. Then, theoperations are repeated again until all data blocks of the receivedportion of the audio signal have been processed (compressed) andmultiplexed 128 onto the transmission bit stream.

Continuing to refer to FIG. 1, on selection, a prediction filter isapplied 110 to the unit (block or sub-block) of audio data to beprocessed and compressed. Similar to the block/sub-block sizeinformation, the parameters of the prediction filter are conveyed112-114 to the recipient (e.g. multiplexed 128 onto the transmission bitstream).

In various embodiments, the filtering may be assisted by the employmentof neighboring blocks. In various embodiments, the prediction filter isa Linear Prediction Filter, and the parameters are the prediction orderp, and the prediction coefficients a₁, . . . a_(p). In variousembodiments, the parameters conveyed 112-114 to the recipient mayinclude the prediction order p, the quantization step size use toquantize prediction coefficients, and the quantized predictioncoefficients â₁, . . . , â_(p).

As illustrated, for the embodiments, as a result of the application ofthe prediction filter to the unit of audio data, residual samples e₁, .. . e_(n) are generated 116. Next, a number of statistical measures aredetermined for the residual samples to characterize 118 theirdistribution (to be described more fully below). For the embodiment, thestatistical measures are employed to form 120 a distribution descriptor(also to be described more fully below), which in turn is conveyed tothe recipient (e.g. multiplexed onto the transmission bit stream).Further, for the embodiment, the statistical measures are employed toselect 122 a distribution known to the recipient, and an identifier ofthe selected distribution is conveyed to the recipient (e.g. multiplexed128 onto the transmission bit stream). In various embodiments, thedistribution descriptor also serves as the identifier of the selecteddistribution. In particular, it is used as an index into an array ofknown distribution stored at the recipient.

In various embodiments, the statistical measures determined include amean value of the residual samples, their variances, the skewness oftheir distribution, and the kurtosis of their distribution. In otherembodiments, the invention may be practiced with more or lessstatistical measures.

Still referring to FIG. 1, for the embodiment, the determinedstatistical measures are also employed to divide each residual sampleinto two portions, a most significant bits (MSB) portion, and a leastsignificant bit (LSB) portion (to be described more fully below). Forthe embodiments, the LSB of each residual sample is directly transmittedto the recipient (e.g., multiplexed 128 onto the transmission bit streamwithout encoding). For the embodiments, the number of LSB of eachresidual sample being directly transmitted to the recipient is alsoconveyed to the recipient (e.g., multiplexed 128 onto the transmissionbit stream without encoding).

In various embodiments, the mean DC offset, if applicable, is alsocomputed, and conveyed to the recipient (e.g., multiplexed 128 onto thetransmission bit stream without encoding). For these embodiments, DCoffset is subtracted from the residual samples.

Further, the MSBs of each residual sample are encoded 122-124 usingcodewords (or simply, codes) constructed using the selecteddistribution. The encoded MSBs are then provided to the recipient (e.g.,multiplexed 128 onto the transmission bit stream without encoding). Invarious embodiments, the constructed codes may be Huffman codes, runlength codes, adaptive arithmetic codes, non-adaptive arithmetic codes(e.g. Gilbert-Moore codes), or other codes of the like.

In the foregoing description, the conveyance to the recipient (e.g.,multiplexed 128 onto the transmission bit stream) of the various values,block sizes, prediction order, quantization sizes, quantized predictioncoefficients, distribution identifier, distribution descriptor, thenumber of LSB of each residual sample to be conveyed, the LSB, theencoded MSB, and so forth, are immediately described following thedescription of their generations. The order of presentation is merelyfor ease of understanding. The order of these descriptions is not to beread as limiting on the invention, requiring their conveyance ongeneration. The generated values may be stored, and processed into atransmission bit stream in batch. Further, multiple transmission bitstream, and/or multiple channels (of like or different kinds) may beemployed for the transmission.

Referring now to the statistical measure determination 118, the LSBidentification 126, and the MSB encoding 124 operations again, anembodiment of these operations will be described in further detail.Recall the received audio data are first partitioned 104 in to blocks orsub-blocks, and the blocks/sub-blocks are selected for processing, oneblock/sub-block at time. Assume the selected unit (block/sub-block) hasa size of n, and the residual samples of this unit are e₁ . . . e_(n).

For the earlier described embodiment, where four statistical measures,the mean value of the residual sample, their variances, the skewness ofthe their distribution, and the kurtosis of their distribution, arecomputed, the computations are performed in accordance with thefollowing formulas:

mean value of the residuals:

${\overset{\_}{e} = {\frac{1}{n}{\sum\limits_{i = 1}^{n}x_{i}}}};$

standard deviation of the residual's distribution: σ=√{square root over(var e)}, where

${{{var}\; e} = {\frac{1}{n - 1}{\sum\limits_{i = 1}^{n}\left( {e_{i} - \overset{\_}{e}} \right)^{2}}}};$

skeweness of the distribution:

${{{skew}\mspace{14mu} e} = {\frac{1}{n}{\sum\limits_{i = 1}^{n}\left\lbrack \frac{e_{i} - \overset{\_}{e}}{\sigma} \right\rbrack^{3}}}};$and

kurtosis of the distribution:

${{kurt}\mspace{14mu} e} = {{\frac{1}{n}{\sum\limits_{i = 1}^{n}\left\lbrack \frac{e_{i} - \overset{\_}{e}}{\sigma} \right\rbrack^{4}}} - 3.}$

Further, the distribution descriptor is formed as follows (with thequantized versions) of these quantities:dsc=dsc( e , log₂ σ,skew e,kurt e).

In alternate embodiments, e.g. embodiments offering low-complexitymodes, kurt e=0; skew e=0; ē=0 instead of calculating them properly.

Further, in various alternate embodiments, parameter σ may be estimatedby using absolute deviation or absolute mean of the residual:

$\begin{matrix}{\sigma^{\prime} = {C_{1}\frac{1}{n}{\sum\limits_{i = 1}^{n}{{e_{i} - \overset{\_}{e}}}}}} & (a)\end{matrix}$or.

$\begin{matrix}{\sigma^{''} = {C_{1}\frac{1}{n}{\sum\limits_{i = 1}^{n}{e_{i}}}}} & (b)\end{matrix}$(under assumption that ē→0),

where C₁ is a constant chosen in view of the distribution (e.g. for zeromean Laplacian distribution, C₁ may be set to 1/sqrt(2)).

Further, in various embodiments, the distribution descriptor may beformed using

(i) only variance estimate (e.g. when mean=0) (optionally, using e.g.the (b) variance estimate approach described above),

(ii) variance+mean estimates (optionally, using e.g. the (c) varianceestimate approach described above).

In various embodiments, on determination of the statistical measures,and selection of the distribution, an inverse-quantized mean value

ē

, and the logarithm of standard deviation log₂ σ of the distribution

log₂ σ

are reconstructed.

Then, the reconstructed values are employed to split each residualsample into MSB and LSB as follows:e _(i) ^(MSB)=(e _(i)−

e

)>>max(<log₂ σ>−C₂,0);e _(i) ^(LSB)=(e _(i)−

e

)&((1<<max(<log₂ σ>−C₂,0))−1);

where C₂ is an empirically selected constant. In various embodiments, C₂is set to equal 3.

During decoding, each residual sample will be recombined as follows:e _(i) =e _(i) ^(MSB)<<max<log₂ σ>−C₂,0))+e _(i) ^(LSB)+

e

.

where C₂ is an empirically selected constant. In various embodiments, C₂is set to equal 3.

In various embodiments, the distribution descriptor is also theidentifier of the selected distribution, as it indexes into an array ofpre-stored distributions of the MSBs of the residual samples, at boththe sender and the recipient.

In various embodiments, the ranges of MSBs in these pre-storeddistributions are restricted to [−21,21], which approximatelycorresponds to the range of [−3σ,3σ] in the non-normalized distribution.

As described earlier, the selected distribution is used to constructblock codes for encoding of the MSBs of the residual samples. Their LSBswill be transmitted directly using max (

log₂ σ

C₂, 0) bits for each residual sample. To encode samples which MSBs falloutside the [−ē{MSB}_(max), ē{MSB}_(max)] range, for the embodiment, theencoder transmits an escape code (ē{MSB}_(max)+1), and then uses anystandard monotonic code (e.g. Golomb codes, Golomb-Rice codes,Levenstein code, etc.) to transmit the difference |e_(i) ^(MSB)| and theescape code.

Referring now to FIG. 3, wherein a method view illustrating a method forcompressing the residual signal in accordance with some embodiments isshown. The method may be practiced in conjunction with the method ofFIG. 1 or with other audio/video signal/data compression techniques

As illustrated, at block 304, a block of residual samples 302 ispartitioned into smaller subblocks. Next, a description of the partitionis formed, block 306, and the description of such a partition istransmitted as a side information, or encoded 308 and multiplexed 322into bitstream 324. In various embodiments, the description of thepartition is given for the number of sub-blocks, all of which may beequally sized. In other embodiments, the description of the partition isgiven in the form of a binary-tree-type description, where the totalsize of the block (which may be equal to a power of 2) and smallestacceptable size of the sub-block are specified.

Additionally, for each sub-block, the descriptor of the distribution ofresidual data is calculated, block 312. In a most general case, suchdescriptor may be a continuous function of a sufficient statistic of thedistribution. In various embodiments, it may be a continuous function ofthe sample variance of the distribution, e.g. a logarithm of the samplevariance of the distribution. In other embodiments, it may be acontinuous function of a sample absolute mean of the distribution, e.g.a logarithm of the sample absolute mean of the distribution. In variousembodiments, each of these statistics may be computed as earlierdescribed.

In various embodiments, distribution descriptors for subblocks areencoded differently based on whether the encoding is dealing with thefirst subblock in the bitstream (or random-access-enables segment of thebistream) or it is a subsequent one, blocks 314, 316, and 318. In a caseof first subblock 314, its distribution descriptor may be encoded as is,without any contexts of prediction information, block 316. In a case ofthe subsequent subblocks 314, their descriptors may be codedpredictively, using prior subblocks, block 318. In various embodiments,such prediction may be implemented as a difference between currentdescriptor and the one corresponding to the prior subblock. In alternateembodiments, the Golomb-Rice codes are used to encode such differencesbetween descriptors.

Further, the residual samples in each subblock are encoded usingspecifically selected distributions, provided by their correspondingdistribution descriptors, block 320. In various embodiments, theencoding is performed using one or more known coding techniques, such asHuffman codes (in specific case, Golomb-Rice codes), Gilbert-Moore(arithmetic) codes, Fixed-lengths codes, and combinations thereof.

As with the encoded partition descriptors, the encoded components aremultiplexed into the continuous bitstream and transmitted, blocks322-324.

Referring now to FIG. 2, wherein a system having a transmit section anda receive section, both adapted to practice the compression methods ofFIG. 1 and/or FIG. 3, in accordance with some embodiments, is shown. Inalternate embodiments, a system may comprise only the transmit sectionor the receive section. It is not necessary to always practice theinvention with both sections.

As illustrated, for the embodiments, system 200 comprise transmitsection 202 including transmitter 216, and a receive section 222including receiver 226. In alternate embodiments, transmit and receivesections may share a common transceiver. Further, for the embodiments,in addition to transmitter 216, transmit section 202 includes controller218, whereas in addition to receiver 226, receive section 222 includescontroller 230, to control the operations of the various elements of therespective sections. Similarly, in alternate embodiments, transmit andreceive sections may share a common controller instead.

For the embodiment, in addition to transmitter 216 and controller 218,transmit section 202 further includes first selector 206, filter 208,encoder 212, computer unit 210, and second selector 214, coupled to eachother, and to transmitter 216 and controller 218 as shown. Selector 206is employed, under the control of controller 218 to partition a portionof a stream of audio signal data into blocks or sub-blocks. Filter 208is a prediction filter, to be applied, under the control of controller218, to the current of audio signal data to be processed and compressed.Compute unit 210 under the control of controller 218 is employed toperform the various earlier described computations. Encoder 212 isemployed under the control of controller 218 to encode the MSB of theresidual samples as earlier described. Second selector 214 under thecontrol of controller 218 is employed to select the various outputvalues to be outputted, and multiplexed them onto the transmission bitstream.

For the embodiment, in addition to receiver 226 and controller 230,receive section 222 further includes decoder 228, and recombiner 232,coupled to each other, and to receiver 226 and controller 230 as shown.Decoder 228, under the control of controller 230, is employed to decodethe encoded MSB of the residual samples as earlier described. Recombiner232 is employed, under the control of controller 230, to recombine thereceived MSB and LSB to reconstitute the residual sample.

In various embodiments, encoder 212 is also adapted to practice themethod illustrated by FIG. 3, i.e. partitioning the residual data of anunit of audio signal data into subblocks, determining the distributionsof the subblocks, and encoding the subblocks based at least in part onthe determined distributions to reduce the amount of data having to betransmitted by transmitter 216.

Except for the logic provided to these elements and/or their usage tocooperate with other elements to effectuate the desired compression ofaudio signal, these elements otherwise may be implemented in a varietyof manners, in hardware, firmware, software, or combination thereof.Thus, system 200 represents a broad of range of systems having audiotransmission and/or audio reception capabilities. For examples, system200 may be a wireless mobile phone, a palm-sized computer, a tabletcomputer, a laptop computer, a desktop computer, a server, a set-topbox, an audio/video entertainment unit, a music player, a DVD player, aCD player, a CAMCORDER, and so forth.

Thus, a novel audio signal data compression method and apparatus hasbeen described. Although specific embodiments have been illustrated anddescribed herein, it will be appreciated by those of ordinary skill inthe art that a wide variety of alternate and/or equivalentimplementations may be substituted for the specific embodiments shownand described, without departing from the scope of the presentinvention. This application is intended to cover any adaptations orvariations of the embodiments discussed herein. Therefore, it ismanifestly intended that this invention be limited only by the claimsand the equivalents thereof.

1. A computer-implemented audio bit stream decoding method comprising:processing by the computer a bit stream received from a transmissiondevice, said bit stream representing in substance a unit of audio signaldata, said bit stream comprising an encoded subblock of residual data,said subblock having been partitioned from a block of said residualdata, said block of said residual data having been generated fromapplying a prediction filter to a block or a subblock of audio signaldata, said subblock of residual data having been encoded utilizing aplurality of statistical measures characterizing a distribution of saidsubblock of residual data to assist in reducing an amount of data havingto be included in said bit stream, said plurality of statisticalmeasures including at least two of: a mean of said subblock of residualdata, a variance of said subblock of residual data, an estimate of saidvariance, a skewness of said distribution, and a kurtosis of saiddistribution; determining, by the computer according to said bit stream,said plurality of statistical measures characterizing said distributionof said subblock of residual data; and reconstructing in substance saidsubblock of residual data, by the computer, according to said encodedsubblock of residual data and said determined plurality of statisticalmeasures characterizing said distribution of said subblock of residualdata.
 2. The method of claim 1, wherein said bit stream furthercomprises a plurality of additional encoded subblocks of residual datapartitioned said block of said residual data.
 3. The method of claim 2,wherein the method further comprises performing the determining andreconstructing operations of claim 1 for each of said plurality ofadditional encoded subblocks of residual data.
 4. The method of claim 2,wherein said bit stream further comprises a description of thepartitioning in a selected one of an un-encoded and encoded form.
 5. Themethod of claim 1, wherein determining said plurality of statisticalmeasures characterizing said distribution of said subblock of residualdata comprises processing a distribution descriptor included in said bitstream and associated with said encoded subblock of residual data, saiddistribution descriptor based at least in part on said plurality ofstatistical measures characterizing said distribution of said subblockof residual data.
 6. The method of claim 5, wherein processing saiddistribution descriptor comprises decoding an encoded distributiondescriptor if said subblock is a first subblock of residual data encodedin said bit stream.
 7. The method of claim 5, wherein processing saiddistribution descriptor comprises decoding an encoded difference ordifferences between said distribution descriptor and a distributiondescriptor of a prior subblock of the residual data if said subblock isnot a first subblock of residual data encoded in said bit stream.
 8. Themethod of claim 7, wherein decoding said encoded difference ordifferences comprises processing a Golomb-Rice code included in said bitstream.
 9. The method of claim 5, wherein processing said distributiondescriptor comprises processing an un-encoded distribution descriptor.10. The method of claim 1, wherein reconstructing in substance saidsubblock of residual data comprises processing a selected one of Huffmancodes and run-length codes, included in said bit stream, to decode theencoded subblock of the residual data, based at least in part on saiddistribution.
 11. The method of claim 1, wherein reconstructing insubstance said subblock of residual data comprises processing a selectedone of Gilbert-Moore codes and arithmetic codes, included in said bitstream, to decode the encoded subblock of the residual data, based atleast in part on said distribution.
 12. An audio bit stream decodercomprising means for processing a bit stream received from atransmission device, said bit stream representing in substance a unit ofaudio signal data, said bit stream comprising an encoded subblock ofresidual data, said subblock having been partitioned from a block ofsaid residual data, said block of said residual data having beengenerated from applying a prediction filter to a block or a subblock ofaudio signal data, said subblock of residual data having been encodedutilizing a plurality of statistical measures characterizing adistribution of said subblock of residual data to assist in reducing anamount of data having to be included in said bit stream, said pluralityof statistical measures including at least two of: a mean of saidsubblock of residual data, a variance of said subblock of residual data,an estimate of said variance, a skewness of said distribution, and akurtosis of said distribution; means for determining, according to saidbit stream, said plurality of statistical measures characterizing saiddistribution of said subblock of residual data; and means forreconstructing in substance said subblock of residual data according tosaid encoded subblock of residual data and said determined plurality ofstatistical measures characterizing said distribution of said subblockof residual data.
 13. The decoder of claim 12, wherein said means fordetermining is further adapted to determine said plurality ofstatistical measures by processing a distribution descriptor included insaid bit stream and associated with said encoded subblock of residualdata, said distribution descriptor based at least in part on saidplurality of statistical measures characterizing said distribution ofsaid subblock of residual data.
 14. The decoder of claim 13, whereinsaid means for determining is further adapted to determine saidplurality of statistical measures by decoding an encoded distributiondescriptor if said subblock is a first subblock of residual dataincluded in said bit stream.
 15. The decoder of claim 13, wherein saidmeans for determining is further adapted to determine said plurality ofstatistical measures by determining a difference or differences betweensaid distribution descriptor and a distribution descriptor of a priorsubblock of said residual data if said subblock is not a first subblockof residual data included in said bit stream.
 16. The decoder of claim15, wherein said means for determining is further adapted to useGolomb-Rice codes to determine said plurality of statistical measures bydetermining a difference or differences between said distributiondescriptor and a distribution descriptor of a prior subblock of saidresidual data if said subblock is not a first subblock of residual dataincluded in said bit stream.
 17. A computing system comprising: areceiving component adapted to receive a bit stream representing insubstance a unit of audio signal data from a transmission device; aprocessing component coupled to said receiving component and adapted toprocess said bit stream, said bit stream comprising an encoded subblockof residual data, said subblock having been partitioned from a block ofsaid residual data, said block of said residual data having beengenerated from applying a prediction filter to a block or a subblock ofaudio signal data, said subblock of residual data having been encodedutilizing a plurality of statistical measures characterizing adistribution of said subblock of residual data to assist in reducing anamount of data having to be included in said bit stream, said pluralityof statistical measures including at least two of: a mean of saidsubblock of residual data, a variance of said subblock of residual data,an estimate of said variance, a skewness of said distribution, and akurtosis of said distribution; a determining component coupled to saidprocessing component and adapted to determine, according to said bitstream, said plurality of statistical measures characterizing saiddistribution of said subblock of residual data; and a reconstructingcomponent coupled to said determining component and adapted toreconstruct in substance said subblock of residual data according tosaid encoded subblock of residual data and said determined plurality ofstatistical measures characterizing said distribution of said subblockof residual data.
 18. The system of claim 17, wherein said determiningcomponent is further adapted to determine said plurality of statisticalmeasures by processing a distribution descriptor included in said bitstream and associated with said encoded subblock of residual data, saiddistribution descriptor based at least in part on said plurality ofstatistical measures characterizing said distribution of said subblockof residual data.
 19. The system of claim 18, wherein said determiningcomponent is further adapted to determine said plurality of statisticalmeasures by decoding an encoded distribution descriptor if said subblockis a first subblock of residual data included in said bit stream. 20.The system of claim 18, wherein said determining component is furtheradapted to determine said plurality of statistical measures bydetermining a difference or differences between said distributiondescriptor and a distribution descriptor of a prior subblock of saidresidual data if said subblock is not a first subblock of residual dataincluded in said bit stream.
 21. The system of claim 20, wherein saiddetermining component is further adapted to use Golomb-Rice codes todetermine said plurality of statistical measures by determining adifference or differences between said distribution descriptor and adistribution descriptor of a prior subblock of said residual data ifsaid subblock is not a first subblock of residual data included in saidbit stream.
 22. The system of claim 17, wherein the system is selectedfrom a group consisting of a wireless mobile phone, a palm-sizedcomputer, a tablet computer, a laptop computer, a desktop computer, aserver, a set-top box, an audio/video entertainment unit, a musicplayer, a DVD player, a CD player, and a CAMCORDER.